Formation and Analysis of Optimal Interbank Networks under Liquidity Shocks: A Decentralized vs. Centralized Approach
Decentralized interbank networks, while individually optimal for banks, lead to lower overall liquidity and higher systemic risk compared to a centralized network managed by a social planner aiming to maximize total welfare.
Evaluating Large Language Model Outputs: Comparing Criteria Developed by Domain Experts, Lay Users, and the Models Themselves
Domain experts, lay users, and Large Language Models (LLMs) develop distinct sets of evaluation criteria for assessing LLM outputs, with domain experts providing the most detailed and specific criteria, lay users emphasizing formatting and clarity, and LLMs generating more generalized criteria based on prompt keywords.
대학 컴퓨터 과학 시험을 통한 대규모 언어 모델의 과학적 능력 평가
대규모 언어 모델의 과학적 문제 해결 능력을 평가하기 위해 대학 컴퓨터 과학 시험 문제를 활용한 벤치마크 SciEx를 제안하였다. SciEx는 다국어, 다모달 문제를 포함하며, 전문가 채점과 자동 채점을 제공한다. 실험 결과, 현재 대규모 언어 모델은 대학 시험 문제를 해결하는 데 여전히 어려움을 겪고 있지만, 채점 능력은 전문가 수준에 근접한 것으로 나타났다.
Evaluating the Reliability of Automatic Methods for Assessing Instruction-Tuned Large Language Models
Automatic evaluation methods based on text overlap and language model judgments can approximate human ratings under specific conditions, but their reliability is highly context-dependent.
Uncorrelated Uncertainty Assumption and Statistical Taylor Expansion for Analyzing Measurement Errors
Statistical Taylor expansion provides a framework to calculate the mean and variance of an analytic function with imprecise input variables, based on the uncorrelated uncertainty assumption that each input variable is measured independently with fine enough statistical precision.
Achieving Quantum Supremacy: Google Quantum AI's Pioneering Efforts in Superconducting Quantum Computers
Google Quantum AI has been at the forefront of driving the development of practical quantum computers, culminating in the landmark achievement of quantum supremacy in 2019 using their 53-qubit Sycamore processor.
Exploring Productivity, Research Topics, and Collaboration Patterns in Information Retrieval: Insights from Academia, Industry, and Cross-Community Partnerships
Academic research, industry research, and collaborative research between academia and industry in information retrieval focus on different topics. Academia-Industry Collaboration is more oriented towards large teamwork, and the field of information retrieval has become richer over time in terms of themes, foci, and sub-themes.
Evaluating the Impact of Automation on Learning Outcomes: A Comparative Study of LLM Chatbots, Search Engines, and Textbooks
While LLM-based chatbots can support comprehensive understanding of key concepts, they are less effective than textbooks in promoting long-term knowledge retention. Academic performance impacts both learning outcomes and search patterns, with higher-competence learners engaging more deeply with content through reading-intensive behaviors.
Comprehensive Evaluation of Large Language Models' String Processing Capabilities
Large language models (LLMs) struggle to accurately process strings compared to human capability, despite their advancements in natural language processing tasks.
Energy-Efficient Picosecond Spin-Orbit Torque Magnetization Switching in Ferromagnetic and Ferrimagnetic Films
Spin-orbit torque can efficiently switch the magnetization of ferromagnetic and ferrimagnetic films using ultrashort electrical pulses in the picosecond regime, achieving over an order of magnitude reduction in energy consumption compared to the nanosecond regime.
© 2024 by Linnk AI